Taxometric Analysis of the Toronto Structured Interview for Alexithymia: Further Evidence That Alexithymia Is a Dimensional Construct
Bibliographic record
Abstract
Alexithymia is a clinically relevant personality construct characterized by difficulties identifying and describing feelings, externally oriented thinking, and impoverished imaginal processes. Previous taxometric investigations provided evidence that alexithymia is best conceptualized as a continuous dimension rather than a discrete type, at least when assessed with the self-report 20-Item Toronto Alexithymia Scale. The aim of the current study was to test the categorical versus dimensional structure of alexithymia using the recently developed Toronto Structured Interview for Alexithymia. Three nonredundant taxometric procedures (MAXCOV, MAMBAC, and L-Mode) were performed on the Toronto Structured Interview for Alexithymia subscale scores from a multinational sample of 842 adults. All taxometric procedures produced unambiguously dimensional solutions, providing further evidence that the core alexithymia features are continuously distributed in the population. Discussion focuses on the theoretical, assessment, and clinical implications of these findings for the alexithymia construct.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".